Association between Dyslipidaemia and Cognitive Impairment: A Meta-Analysis of Cohort and Case-Control Studies
Why this work is in the frame
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Bibliographic record
Abstract
Background: This study explored the specific relationship between different lipid indicators and cognitive impairment and aimed to provide a reference for implementing targeted lipid regulation measures to prevent and alleviate cognitive impairment. Methods: We searched three databases (PubMed, Embase, and Web of Science) for literature related to hyperlipidaemia, lipid levels, and cognitive impairment, and used the Newcastle-Ottawa Scale to evaluate the quality of the identified literature. A meta-analysis was performed using RevMan 5.4, and the combined effect size ratio using a random-effects model (odds ratio [OR] and 95% confidence interval [CI]) was used to evaluate the association between dyslipidaemia and cognitive impairment. Results: Among initially identified 2247 papers, we ultimately included 18 studies involving a total of 758,074 patients. The results of the meta-analysis revealed that patients with hyperlipidaemia had a 1.23-fold higher risk of cognitive impairment than those with normal lipid levels (OR = 1.23, 95% CI: 1.04–1.47, p = 0.02). Further subgroup analysis showed that elevated total cholesterol (TC) levels increased the risk of cognitive impairment by 1.59-fold (OR = 1.59, 95% CI: 1.27–2.01, p < 0.0001) and were more significant in older or male patients. Moreover, elevated triglyceride levels were inversely correlated with cognitive disorders, whereas elevated low-density lipoprotein cholesterol levels were unrelated to cognitive impairment risk. Conclusions: Dyslipidaemia was strongly associated with cognitive impairment, and elevated TC levels were a risk factor for cognitive impairment. Furthermore, the damaging effects of elevated TC levels on cognition were more pronounced in older and male populations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it